Online signature verification based on string edit distance
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Authors
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Publication date
2019
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Type
01A - Journal article
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Parent work
International Journal on Document Analysis and Recognition
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Volume
22
Issue / Number
Pages / Duration
41-54
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Publisher / Publishing institution
Springer
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Abstract
Handwritten signatures are widely used and well-accepted biometrics for personal authentication. The accuracy of signature verification systems has significantly improved in the last decade, making it possible to rely on machines in particular cases or to support human experts. Yet, based on only few genuine references, signature verification is still a challenging task. The present paper provides a comprehensive comparison of two prominent string matching algorithms that can be readily used for signature verification. Moreover, it evaluates a recent cost model for string matching which turns out to be particularly well suited for the task of signature verification. On three benchmarking data sets, we show that this model outperforms the two standard models for string matching with statistical significance.
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ISBN
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1433-2825
1433-2833
1433-2833
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
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Peer review of the complete publication
Open access category
Closed
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Citation
Riesen, K., & Schmidt, R. (2019). Online signature verification based on string edit distance. International Journal on Document Analysis and Recognition, 22, 41–54. https://doi.org/10.1007/s10032-019-00316-1